Cooperative surveillance in video sensor networks

Alex Fridman, Richard Primerano, Steven Weber, Moshe Kam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In the energy-constrained medium of video sensor networks, the objective of much research has been to statistically minimize the number of nodes that will achieve a sufficient degree of coverage. We consider increasing the number of nodes beyond the threshold of full coverage, and cooperatively filtering out the high level of redundant data in the video streams to minimize pernode capacity requirements. The scenario we study is that of a swarm of robots, all with wireless communication capabilities. Some of the robots are equipped with video cameras and are thus considered sensors. A few select robots have sufficient battery and computational power to perform machine vision processing of the video stream. The goal of this scenario is to get the video from the sensors to the video-processing robots, which can then extract high-level surveillance information about the observed environment. We present an optimization framework for minimizing redundant visual data transmissions, while maximizing the throughput from sensors to processing nodes. We also characterize through simulation the performance gain on the sensor network as the video coverage increases.

Original languageEnglish (US)
Title of host publication2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008
DOIs
StatePublished - Dec 12 2008
Externally publishedYes
Event2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008 - Palo Alto, CA, United States
Duration: Sep 7 2008Sep 11 2008

Publication series

Name2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008

Other

Other2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008
Country/TerritoryUnited States
CityPalo Alto, CA
Period9/7/089/11/08

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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